code: def _target_layer_specs(self):
      return {
          "fold_id": tf.TensorSpec([1], dtype=tf.int32),
          "gt": tf.TensorSpec([None], dtype=tf.int32),
          "gt_len": tf.TensorSpec([1], dtype=tf.int32),
      }
  
imports: import logging
  import os
  from typing import Type, Optional
  import tensorflow
  from tfaip.data.data import DataBase
  from tfaip.data.databaseparams import DataPipelineParams
  from tfaip.data.pipeline.datapipeline import DataPipeline
  from tfaip.data.pipeline.definitions import PipelineMode, INPUT_PROCESSOR
  from tfaip.data.pipeline.processor.params import SequentialProcessorPipelineParams
  from calamari_ocr.ocr.augmentation.dataaugmentationparams import DataAugmentationAmount
  from calamari_ocr.ocr.dataset.datareader.base import CalamariDataGeneratorParams
  from calamari_ocr.ocr.dataset.datareader.file import FileDataParams
  from calamari_ocr.ocr.dataset.imageprocessors.augmentation import AugmentationProcessorParams
  from calamari_ocr.ocr.dataset.imageprocessors.default_image_processors import default_image_processors
  from calamari_ocr.ocr.dataset.imageprocessors.preparesample import PrepareSampleProcessorParams
  from calamari_ocr.ocr.dataset.params import DataParams
  from calamari_ocr.ocr.dataset.pipeline import CalamariPipeline
  from calamari_ocr.ocr.dataset.postprocessors.ctcdecoder import CTCDecoderProcessorParams
  from calamari_ocr.ocr.dataset.postprocessors.reshape import ReshapeOutputsProcessorParams
  from calamari_ocr.ocr.dataset.textprocessors.default_text_processor import default_text_pre_processors
  from calamari_ocr.utils.image import ImageLoaderParams
label_desc: Use image node_id 4 for calling the Data obj's underlying member method code with example usage: obj._target_layer_specs() and returns: dict